We examine drivers of cost overruns in Norwegian development projects in the oil and gas sector. The multivariate longitudinal econometric analysis employs a unique and detailed dataset consisting of 80 different projects between 2000 and 2015. Among the significant results, we find that the...

The oil and gas sector plays a crucial role in the Norwegian economy. It accounts for a very large proportion of gross domestic product, government revenues, investment and exports. A sharp fall in oil prices has had a significant impact on the economy and focused great attention on the cost...

Focusing on the characteristics of destinations, this paper pursues to identify the role of spatial spillovers in driving location choices of manufacturing and services' firms. With this objective a spatial conditional logit framework is defined, allowing for neighbourhood-related spatial...

We investigate the potential for statistical forecasting of aggregate oil and gas investment on the Norwegian Continental Shelf (NCS). A unique and detailed dataset containing data from 109 different fields on the NCS between 1970 and 2015 was employed. A set of 1080 autoregressive distributed...

We examine the determinants of product, process, and organizational innovation, and their impact on firm labor productivity using data from a unique innovation survey of firms in Pakistan. We find significant heterogeneity in the impact of different innovations on labor productivity:...

This paper uses firm-level survey data to explore whether the extent to which firms perceive taxes and crime as impediments to their operations and growth (perceived constraints) affects firm tax evasion. To rule out spurious covariation, I use reported crime incidences as an instrumental...

Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis. This paper presents an example where nonparametric flexibility can be...

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors is assumed. Two specializations of GMM are...

Due to their indeterminacies, static and dynamic factor models require identifying assumptions to guarantee uniqueness of the parameter estimates. The indeterminacy of the parameter estimates with respect to orthogonal transformations is known as the rotation problem. The typical strategy in...

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step, but retain a fully nonparametric specification in the first step. Such estimators exist in many economic applications, including a wide range of missing data and...